Screening For Early Disease Research Articles

Predicting time to prostate cancer recurrence based on joint models for non‐linear longitudinal biomarkers and event time outcomes

Biological markers that are both sensitive and specific for tumour regrowth or metastasis are increasingly becoming available and routinely monitored during the regular follow-up of patients treated for cancer. Obtained by a simple blood test, these markers provide an inexpensive non-invasive means for the early detection of recurrence (or progression). Currently, the longitudinal behaviour of the marker is viewed as an indicator of early disease progression, and is applied by a physician in making clinical decisions. One marker that has been studied for use in both population screening for early disease and for detection of recurrence in prostate cancer patients is PSA. The elevation of PSA levels is known to precede clinically detectable recurrence by 2 to 5 years, and current clinical practice often relies partially on multiple recent rises in PSA to trigger a change in treatment. However, the longitudinal trajectory for individual markers is often non-linear; in many cases there is a decline immediately following radiation therapy or surgery, a plateau during remission, followed by an exponential rise following the recurrence of the cancer. The aim of this article is to determine the multiple aspects of the longitudinal PSA biomarker trajectory that can be most sensitive for predicting time to clinical recurrence. Joint Bayesian models for the longitudinal measures and event times are utilized based on non-linear hierarchical models, implied by unknown change-points, for the longitudinal trajectories, and a Cox proportional hazard model for progression times, with functionals of the longitudinal parameters as covariates in the Cox model. Using Markov chain Monte Carlo sampling schemes, the joint model is fit to longitudinal PSA measures from 676 patients treated at Massachusetts General Hospital between the years 1988 and 1995 with follow-up to 1999. Based on these data, predictive schemes for detecting cancer recurrence in new patients based on their longitudinal trajectory are derived.

FAMILIAL BREAST AND OVARIAN CANCER: THE ROLE OF THE BRCA GENES

Sporadic breast cancer and ovarian cancer constitute two of the top four cancers occurring in women in the 1990s. Familial forms of these diseases also have been recognized; breast cancer is heritable in 5–10% of cases and ovarian cancer in 3–13% of cases. Screening for early disease has been useful for breast cancers but not for ovarian cancers. Genetic testing allows for predicting who will be at risk for developing either disease. The Breast Cancer (BRCA) genes are thought to be involved in 99% of all combined familial breast and ovarian cancers; the best defined gene is BRCA1. The presence of a mutated BRCA1 allele confers a lifetime risk of breast cancer of 70–80% and a risk of ovarian cancer of 40–50%. Individuals with this mutation also have an increased risk of developing colon, prostate, and pancreatic cancer. Genetic analysis for these genes is complex, and management of the information gained from testing needs to be handled with care. Nonetheless, the discovery of the BRCA genes and the determination of their role in familial breast and ovarian cancers represent major steps in cancer prevention.